Hi,

I am currently running regressions by group and saving coefficients using "statsby". It turns out that I need to loop over it many times and it takes way to long.

1) I have seen that there exist an alternative: "statsbyfast" but I could not get it to work " (I am using Stata 16, curious if it works at all?)
Code:
.         statsbyfast _se, by(date) saving(beta_model`t', replace): regress F1_exret `model`t''
_se command not found
2) I have seen another alternative: "runby". I would like to substitute "statsby" by "runby" but I do not know how to save regression estimated coefficients.

Code:
* Example generated by -dataex-. To install: ssc install dataex
clear
input float date double stock float(F1_exret LogSize LogBM MOM12)
420 1   1.927711  -.5852472   .11499815           0
421 1   2.651725  -.6215999   .16694237           0
422 1   8.454855  -.6135978    .1723073           0
423 1   2.894461  -.5747078   .06242105           0
424 1  -5.920187  -.5773819    .0719837           0
425 1     -.0375  -.6260327   .22071365           0
426 1 -4.4817386  -.6695028   .28219923           0
427 1   3.252563  -.7185428    .3852584           0
428 1   -3.22287  -.7098303    .3655157           0
429 1   7.776516  -.7125176    .3677585           0
430 1  1.1862323  -.6888025   .34420845           0
431 1   2.388549  -.6969711    .3597388           0
432 1   7.000864  -.6892462    .3669921           0
433 1  1.0732287  -.6497501   .28905886  -.59001756
434 1   .5136925  -.6521176   .29533115  -.34324735
435 1   5.910722   -.680016    .3228189  -.33748865
436 1    .484852  -.6565322    .2706667  -.52697074
437 1  -6.739183  -.6319041   .24997833   -.3791255
438 1 -2.2547672  -.6268925   .23821585  -.13331884
439 1  -2.883452  -.6760791    .3425798   .00319561
440 1   11.08221  -.7308719    .4584391 -.014854454
441 1 -.57737654  -.6569486    .2996624   -.2899106
442 1 -1.1008954  -.6990199    .4086685   .07938184
443 1    14.4762  -.7098561    .4065881   -.2690085
444 1 -.53210557  -.6391733    .3055489   -.2858834
445 1   -2.40546   -.644307    .3291195   .06347923
446 1   5.783891  -.6296629    .2995791   -.1533446
447 1   5.910736 -.58641416   .24357404  -.09942824
448 1  12.571774   -.597588   .27519906   .09329037
449 1   6.725173  -.5423116   .17339425  -.09669264
450 1  1.3984214  -.5455991    .1990709   .14503703
451 1   3.005836      -.543    .1645017    .1002197
452 1 -3.1606004   -.571285    .2072771    .4447244
453 1  -.4027479  -.5637179    .1794863    .6573465
454 1   5.554266  -.5739741    .2261642    .3271194
455 1   3.898304 -.54304373    .1708042    .5298603
456 1   .4512345  -.5130402   .20538726    .7006333
457 1  13.428807  -.5485587   .29233277    .4738248
458 1   8.651517  -.5060327   .18044583   .15185186
459 1 -1.7802713  -.4690668    .0826417    .3331818
460 1 -2.2094834  -.4564817  .062599584   .51906013
461 1    9.96819  -.4611211   .11156975    .5783971
462 1 -13.923313  -.3763591  -.10043382   .15692236
463 1  1.5749156  -.3523002   -.1325143   .40620375
464 1  13.581646    -.39034  -.05852994    .4733673
465 1  -.9079541  -.3641424  -.11021375    .4876685
466 1  28.189796  -.4037958 -.025893386    .7512823
467 1 -14.805963 -.28380394   -.2747483    .6154183
468 1  -2.969713   -.377814  .005564627   1.0093682
469 1   11.17293  -.3710982 -.008095614    .2032261
470 1   8.292903  -.3246959  -.09919195    .4272633
471 1 -1.7403984  -.3214875  -.12235998    .3403799
472 1 -2.7151685  -.3393546  -.12690166   .17146797
473 1  -7.766134  -.3716588  -.02381942   .15479617
474 1  -15.99229 -.40318274  .032537498   .09050763
475 1 -12.498517  -.4943248   .22291256  -.20170324
476 1  -2.534053 -.55512065    .3356217   -.3868619
477 1  -2.259816  -.5680073    .3793441   -.4242548
478 1   8.037499  -.6040637    .4178481   -.5078657
479 1  2.4049914  -.5842053    .3603639   -.4787201
480 1 -15.215885  -.5496637    .2613597  -.52056396
481 1  33.767292  -.6454348    .4032734   -.4723427
482 1  11.540565  -.5160571    .1818769   -.4544776
483 1   -7.46128  -.4515151    .0549905   -.4670102
484 1 -17.403605  -.5020388   .16492245   -.4069193
485 1  4.2902956  -.6083258    .3649641   -.4951222
486 1   -4.89105  -.5918792    .3482355   -.5645494
487 1 -4.3433957  -.6647894     .469943  -.54739916
488 1  .26728684  -.6823717    .5128142  -.49472445
489 1   2.872766  -.6869114    .5169506   -.4356141
490 1   7.375127  -.6433847   .45524135   -.4245361
491 1  .12276764  -.6433478    .4670534   -.3215246
492 1   8.740447  -.6436945    .5953303   -.3798505
493 1  -7.108429 -.58352727    .4839517   -.5499729
494 1   7.625951 -.58401996    .4908611  .002041269
495 1    7.67378   -.605188   .50103056   -.4688245
496 1   .2178242  -.5843823    .4542759   -.6478162
497 1  -10.95345  -.5801749    .4198487    -.385942
498 1 -10.099359  -.6432791    .5603625 -.016407905
499 1 -1.0133773  -.6964951    .6791326   -.3039938
500 1  2.0545838  -.6054888    .5074692  -.23619685
501 1   6.788255    -.64476    .5387905   .07837227
502 1   9.634001  -.6598168    .5455746   .04100154
503 1 -12.522242  -.6306199    .4771652  -.08651516
504 1   2.734117  -.7173976    .6910625 -.009167857
505 1  1.1132321  -.6889408     .650866  -.24872683
506 1  -7.731453   -.728283    .7263799   -.4354232
507 1   3.013713  -.7662435    .7858039   -.5364927
508 1 -2.5123286  -.7174132     .710502   -.6678619
509 1 -1.7303873  -.6940764    .6530726   -.6644319
510 1 -4.0352745  -.6226304   .49954605   -.6289694
511 1  -11.12212  -.6619639   .57828003  -.12466832
512 1 -14.533053  -.6750892    .5982243 -.016238984
513 1  13.764318  -.8019307     .850649   -.3836236
514 1  -2.738305  -.7958064    .8558486   -.7865438
515 1  -4.768898  -.7803991     .804569   -.7178196
516 1  -5.050323  -.7936473    .7874112   -.7926201
517 1   .1005229  -.8161545    .8274837  -.50812155
518 1   7.090696  -.8396168    .8552675   -.6607589
519 1   16.29535  -.8485509     .879484   -.5640138
end
format %tm date
label values stock unit_id
label def unit_id 1 "130062", modify
Code:
    statsby _b _se, by(date) saving(beta_model1, replace): regress F1_exret LogSize LogBM MOM12
Can someone help me produce the exact same output with "runby"? Thanks!